SoroushVahidi/scidocs huggingface dataset:
HMM-Based Word Alignment in Statistical Translation
(2002)

In this paper, we describe a new model for word alignment in statistical translation and present experimental results. The idea of the model is to make the alignment probabilities dependent on the differences in the alignment positions rather than on the absolute positions. To achieve this goal, the approach uses a first-order Hidden Markov model (HMM) for the word alignment problem as they are used successfully in speech recognition for the time alignment problem. The difference to the time alignment HMM is that there is no monotony constraint for the possible word orderings. We describe the details of the model and test the model on several bilingual corpora.
Background Removal in Image Indexing and Retrieval
(1999)

This paper presents our research in image content based indexing and retrieval, a key technology in digital image libraries. In most of the existing image content-based techniques, image features used for indexing and retrieval are global, features are computed over the entire image. The major problem with the global image feature based retrieval methods is that background features can be easily mistakenly taken as object features. When a user attempts to retrieve images using color features, he/she usually means the color feature of an object or objects of interests contained in the image. The approach we describe in this paper utilizes color clusters for image background analysis. Once the background regions are identified, they are removed from the image indexing procedure; therefore, no longer interfering with the meaningful image content during the retrieval process. The algorithm consists of three major steps of computation, fuzzy clustering, color image segmentation, and background analysis.
Induction of fuzzy rules and membership functions from training examples
(1996)

Most fuzzy controllers and fuzzy expert systems must predefine membership functions and fuzzy inference rules to map numeric data into linguistic variable terms and to make fuzzy reasoning work. In this paper, we propose a general learning method as a framework for automatically deriving membership functions and fuzzy if-then rules from a set of given training examples to rapidly build a prototype fuzzy expert system. Based on the membership functions and the fuzzy rules derived, a corresponding fuzzy inference procedure to process inputs is also developed.
Routing Attacks and Countermeasures in the RPL-Based Internet of Things
(2013)

The Routing Protocol for Low-Power and Lossy Networks (RPL) is a novel routing protocol standardized for constrained environments such as 6LoWPAN networks. Providing security in IPv6/RPL connected 6LoWPANs is challenging because the devices are connected to the untrusted Internet and are resource constrained, the communication links are lossy, and the devices use a set of novel IoT technologies such as RPL, 6LoWPAN, and CoAP/CoAPs. In this paper we provide a comprehensive analysis of IoT technologies and their new security capabilities that can be exploited by attackers or IDSs. One of the major contributions in this paper is our implementation and demonstration of well-known routing attacks against 6LoWPAN networks running RPL as a routing protocol. We implement these attacks in the RPL implementation in the Contiki operating system and demonstrate these attacks in the Cooja simulator. Furthermore, we highlight novel security features in the IPv6 protocol and exemplify the use of these features for intrusion detection in the IoT by implementing a lightweight heartbeat protocol.
Speech emotion classification using tree-structured sparse logistic regression
(2015)

The extraction and selection of acoustic features are crucial steps in the development of a system for classifying emotions in speech. Most works in the field use some kind of prosodic features, often in combination with spectral and glottal features, and select appropriate features in classifying emotions. In the methods, feature choices are mostly made regardless of existing relationships and structures between features. However, considering them can be beneficial, potentially both for interpretability and to improve classification performance. To this end, a structured sparse logistic regression model incorporated with the hierarchical structure of features derived from prosody, spectral envelope, and glottal information is proposed in this paper. The proposed model simultaneously addresses tree-structured sparse feature selection and emotion classification. Evaluation of the proposed model on Berlin emotional database showed substantial improvement over the conventional sparse logistic regression model.
Quantum clustering algorithms
(2007)

By the term "quantization", we refer to the process of using quantum mechanics in order to improve a classical algorithm, usually by making it go faster. In this paper, we initiate the idea of quantizing clustering algorithms by using variations on a celebrated quantum algorithm due to Grover. After having introduced this novel approach to unsupervised learning, we illustrate it with a quantized version of three standard algorithms: divisive clustering, k-medians and an algorithm for the construction of a neighbourhood graph. We obtain a significant speedup compared to the classical approach.
A Comparative Study of Polar Code Constructions for the AWGN Channel
(2015)

We present a comparative study of the performance of various polar code constructions in an additive white Gaussian noise (AWGN) channel. A polar code construction is any algorithm that selects K best among N possible polar bit-channels at the design signal-to-noise-ratio (design-SNR) in terms of bit error rate (BER). Optimal polar code construction is hard and therefore many suboptimal polar code constructions have been proposed at different computational complexities. Polar codes are also non-universal meaning the code changes significantly with the design-SNR. However, it is not known which construction algorithm at what design-SNR constructs the best polar codes. We first present a comprehensive survey of all the well-known polar code constructions along with their full implementations. We then propose a heuristic algorithm to find the best design-SNR for constructing best possible polar codes from a given construction algorithm. The proposed algorithm involves a search among several possible design-SNRs. We finally use our algorithm to perform a comparison of different construction algorithms using extensive simulations. We find that all polar code construction algorithms generate equally good polar codes in an AWGN channel, if the design-SNR is optimized. Keywords—Bhattacharyya bounds, bit-channels, Gaussian approximation, polar codes
False Data Injection Attacks in Control Systems
(2010)

This paper analyzes the effects of false data injection attacks on Control System. We assume that the system, equipped with a Kalman filter and LQG controller, is used to monitor and control a discrete linear time invariant Gaussian system. We further assume that the system is equipped with a failure detector. An attacker wishes to destabilize the system by compromising a subset of sensors and sending corrupted readings to the state estimator. In order to inject fake sensor measurements without being detected the attacker needs to carefully design its inputs to fool the failure detector, since abnormal sensor measurements usually trigger an alarm from the failure detector. We will provide a necessary and sufficient condition under which the attacker could destabilize the system while successfully bypassing the failure detector. A design method for the defender to improve the resilience of the CPS against such kind of false data injection attacks is also provided.
Automatic Text Summarization based on Betweenness Centrality
(2018)

Automatic text summary plays an important role in information retrieval. With a large volume of information, presenting the user only a summary greatly facilitates the search work of the most relevant. Therefore, this task can provide a solution to the problem of information overload. Automatic text summary is a process of automatically creating a compressed version of a certain text that provides useful information for users. This article presents an unsupervised extractive approach based on graphs. The method constructs an indirected weighted graph from the original text by adding a vertex for each sentence, and calculates a weighted edge between each pair of sentences that is based on a similarity/dissimilarity criterion. The main contribution of the work is that we do a study of the impact of a known algorithm for the social network analysis, which allows to analyze large graphs efficiently. As a measure to select the most relevant sentences, we use betweenness centrality. The method was evaluated in an open reference data set of DUC2002 with Rouge scores.
The Abandoned Side of the Internet: Hijacking Internet Resources When Domain Names Expire
(2015)

The vulnerability of the Internet has been demonstrated by prominent IP prefix hijacking events. Major outages such as the China Telecom incident in 2010 stimulate speculations about malicious intentions behind such anomalies. Surprisingly, almost all discussions in the current literature assume that hijacking incidents are enabled by the lack of security mechanisms in the inter-domain routing protocol BGP. In this paper, we discuss an attacker model that accounts for the hijacking of network ownership information stored in Regional Internet Registry (RIR) databases. We show that such threats emerge from abandoned Internet resources (e.g., IP address blocks, AS numbers). When DNS names expire, attackers gain the opportunity to take resource ownership by re-registering domain names that are referenced by corresponding RIR database objects. We argue that this kind of attack is more attractive than conventional hijacking, since the attacker can act in full anonymity on behalf of a victim. Despite corresponding incidents have been observed in the past, current detection techniques are not qualified to deal with these attacks. We show that they are feasible with very little effort, and analyze the risk potential of abandoned Internet resources for the European service region: our findings reveal that currently 73 /24 IP prefixes and 7 ASes are vulnerable to be attacked. We discuss countermeasures and outline research directions towards preventive solutions.
A Modular IoT Platform for Real-Time Indoor Air Quality Monitoring
(2018)

The impact of air quality on health and on life comfort is well established. In many societies, vulnerable elderly and young populations spend most of their time indoors. Therefore, indoor air quality monitoring (IAQM) is of great importance to human health. Engineers and researchers are increasingly focusing their efforts on the design of real-time IAQM systems using wireless sensor networks. This paper presents an end-to-end IAQM system enabling measurement of CO₂, CO, SO₂, NO₂, O₃, Cl₂, ambient temperature, and relative humidity. In IAQM systems, remote users usually use a local gateway to connect wireless sensor nodes in a given monitoring site to the external world for ubiquitous access of data. In this work, the role of the gateway in processing collected air quality data and its reliable dissemination to end-users through a web-server is emphasized. A mechanism for the backup and the restoration of the collected data in the case of Internet outage is presented. The system is adapted to an open-source Internet-of-Things (IoT) web-server platform, called Emoncms, for live monitoring and long-term storage of the collected IAQM data. A modular IAQM architecture is adopted, which results in a smart scalable system that allows seamless integration of various sensing technologies, wireless sensor networks (WSNs) and smart mobile standards. The paper gives full hardware and software details of the proposed solution. Sample IAQM results collected in various locations are also presented to demonstrate the abilities of the system.
A Delegation Framework for Task-Role Based Access Control in WFMS
(2011)

Access control is important for protecting information integrity in workflow management system (WfMS). Compared to conventional access control technology such as discretionary, mandatory, and role-based access control models, task-role-based access control (TRBAC) model, an access control model based on both tasks and roles, meets more requirements for modern enterprise environments. However, few discussions on delegation mechanisms for TRBAC are made. In this paper, a framework considering temporal constraints to improve delegation and help automatic delegation in TRBAC is presented. In the framework, the methodology for delegations requested from both users and WfMS is discussed. The constraints for delegatee selection such as delegation loop and separation of duty (SOD) are addressed. With the framework, a sequence of algorithms for delegation and revocation of tasks are constructed gradually. Finally, a comparison is made between our approach and the representative related works.
Application of AHP and Taguchi loss functions in supply chain
(2010)

Purpose – The purpose of this paper is to develop a decision model to help decision makers with selection of the appropriate supplier. Design/methodology/approach – Supplier selection is a multi-criteria decision-making process encompassing various tangible and intangible factors. Both risks and benefits of using a vendor in supply chain are identified for inclusion in the evaluation process. Since these factors can be objective and subjective, a hybrid approach that applies to both quantitative and qualitative factors is used in the development of the model. Taguchi loss functions are used to measure performance of each supplier candidate with respect to the risks and benefits. Analytical hierarchy process (AHP) is used to determine the relative importance of these factors to the decision maker. The weighted loss scores are then calculated for each supplier by using the relative importance as the weights. The composite weighted loss scores are used for ranking of the suppliers. The supplier with the smallest loss score is recommended for selection. Findings – Inclusion of both risk and benefit categories in the evaluation process provides a comprehensive decision tool. Practical implications – The proposed model provides guidelines for supply chain managers to make an informed decision regarding supplier selection. Originality/value – Combining Taguchi loss function and AHP provides a novel approach for ranking of potential suppliers for outsourcing purposes.
Oscillator-based assistance of cyclical movements: model-based and model-free approaches
(2011)

In this article, we propose a new method for providing assistance during cyclical movements. This method is trajectory-free, in the sense that it provides user assistance irrespective of the performed movement, and requires no other sensing than the assisting robot’s own encoders. The approach is based on adaptive oscillators, i.e., mathematical tools that are capable of learning the high level features (frequency, envelope, etc.) of a periodic input signal. Here we present two experiments that we recently conducted to validate our approach: a simple sinusoidal movement of the elbow, that we designed as a proof-of-concept, and a walking experiment. In both cases, we collected evidence illustrating that our approach indeed assisted healthy subjects during movement execution. Owing to the intrinsic periodicity of daily life movements involving the lower-limbs, we postulate that our approach holds promise for the design of innovative rehabilitation and assistance protocols for the lower-limb, requiring little to no user-specific calibration.
Wechsler Intelligence Scale for Children-IV Conceptual and Interpretive Guide
(2008)

The Wechsler intelligence scales were developed by Dr. David Wechsler, a clinical psychologist with Bellevue Hospital. His initial test, the Wechsler-Bellevue Intelligence Scale, was published in 1939 and was designed to measure intellectual performance by adults. Wechsler constructed the WBIS based on his observation that, at the time, existing intelligence tests for adults were merely adaptations of tests for children and had little face validity for older age groups.
Percutaneous left atrial appendage closure vs warfarin for atrial fibrillation: a randomized clinical trial.
(2014)

IMPORTANCE
While effective in preventing stroke in patients with atrial fibrillation (AF), warfarin is limited by a narrow therapeutic profile, a need for lifelong coagulation monitoring, and multiple drug and diet interactions.


OBJECTIVE
To determine whether a local strategy of mechanical left atrial appendage (LAA) closure was noninferior to warfarin.


DESIGN, SETTING, AND PARTICIPANTS
PROTECT AF was a multicenter, randomized (2:1), unblinded, Bayesian-designed study conducted at 59 hospitals of 707 patients with nonvalvular AF and at least 1 additional stroke risk factor (CHADS2 score ≥1). Enrollment occurred between February 2005 and June 2008 and included 4-year follow-up through October 2012. Noninferiority required a posterior probability greater than 97.5% and superiority a probability of 95% or greater; the noninferiority margin was a rate ratio of 2.0 comparing event rates between treatment groups.


INTERVENTIONS
Left atrial appendage closure with the device (n = 463) or warfarin (n = 244; target international normalized ratio, 2-3).


MAIN OUTCOMES AND MEASURES
A composite efficacy end point including stroke, systemic embolism, and cardiovascular/unexplained death, analyzed by intention-to-treat.


RESULTS
At a mean (SD) follow-up of 3.8 (1.7) years (2621 patient-years), there were 39 events among 463 patients (8.4%) in the device group for a primary event rate of 2.3 events per 100 patient-years, compared with 34 events among 244 patients (13.9%) for a primary event rate of 3.8 events per 100 patient-years with warfarin (rate ratio, 0.60; 95% credible interval, 0.41-1.05), meeting prespecified criteria for both noninferiority (posterior probability, >99.9%) and superiority (posterior probability, 96.0%). Patients in the device group demonstrated lower rates of both cardiovascular mortality (1.0 events per 100 patient-years for the device group [17/463 patients, 3.7%] vs 2.4 events per 100 patient-years with warfarin [22/244 patients, 9.0%]; hazard ratio [HR], 0.40; 95% CI, 0.21-0.75; P = .005) and all-cause mortality (3.2 events per 100 patient-years for the device group [57/466 patients, 12.3%] vs 4.8 events per 100 patient-years with warfarin [44/244 patients, 18.0%]; HR, 0.66; 95% CI, 0.45-0.98; P = .04).


CONCLUSIONS AND RELEVANCE
After 3.8 years of follow-up among patients with nonvalvular AF at elevated risk for stroke, percutaneous LAA closure met criteria for both noninferiority and superiority, compared with warfarin, for preventing the combined outcome of stroke, systemic embolism, and cardiovascular death, as well as superiority for cardiovascular and all-cause mortality.


TRIAL REGISTRATION
clinicaltrials.gov Identifier: NCT00129545.
Gunshot detection and localization using sensor networks
(2013)

Acoustic sensors or sensor networks can be efficiently used to spot and observe targets of interest and have the ability to conclude the exact location of an object or event within the sensor network's coverage range. For the detection and spot estimation of shooter, the schemes of gunshot localization require one or more sensing technologies. In current situation the importance of counter sniper systems cannot be denied. An efficient counter sniper system that can provide immediate shooter location will provide many benefits to our security personnel. In this paper, the Time Difference Of Arrival (TDOA) of Shock Wave and Muzzle Blast is used to estimate the shooter location. The proposed design and algorithm was validated and shooter origin was resolute that was very close to theoretical values. The result shows that the scheme worked very fine and is capable of locating sniper fires very efficiently, competently and effectively. The designed algorithm worked very well and results were found to be very accurately.
Fast Priority Queues for Cached Memory
(1999)

The cache hierarchy prevalent in todays high performance processors has to be taken into account in order to design algorithms that perform well in practice. This paper advocates the adaption of external memory algorithms to this purpose. This idea and the practical issues involved are exemplified by engineering a fast priority queue suited to external memory and cached memory that is based on <i>k</i>-way merging. It improves previous external memory algorithms by constant factors crucial for transferring it to cached memory. Running in the cache hierarchy of a workstation the algorithm is at least two times faster than an optimized implementation of binary heaps and 4-ary heaps for large inputs.
Reverse Nearest Neighbors in Unsupervised Distance-Based Outlier Detection
(2015)

Outlier detection in high-dimensional data presents various challenges resulting from the “curse of dimensionality.” A prevailing view is that distance concentration, i.e., the tendency of distances in high-dimensional data to become indiscernible, hinders the detection of outliers by making distance-based methods label all points as almost equally good outliers. In this paper, we provide evidence supporting the opinion that such a view is too simple, by demonstrating that distance-based methods can produce more contrasting outlier scores in high-dimensional settings. Furthermore, we show that high dimensionality can have a different impact, by reexamining the notion of reverse nearest neighbors in the unsupervised outlier-detection context. Namely, it was recently observed that the distribution of points' reverse-neighbor counts becomes skewed in high dimensions, resulting in the phenomenon known as hubness. We provide insight into how some points (antihubs) appear very infrequently in k-NN lists of other points, and explain the connection between antihubs, outliers, and existing unsupervised outlier-detection methods. By evaluating the classic k-NN method, the angle-based technique designed for high-dimensional data, the density-based local outlier factor and influenced outlierness methods, and antihub-based methods on various synthetic and real-world data sets, we offer novel insight into the usefulness of reverse neighbor counts in unsupervised outlier detection.
CONCEPTUAL REQUIREMENTS FOR THE AUTOMATIC RECONSTRUCTION OF BUILDING INFORMATION MODELS FROM UNINTERPRETED 3 D MODELS
(2009)

A multitude of new applications is quickly emerging in the field of Building Information Models (BIM). BIM models describe buildings with respect to their spatial and especially semantic and thematic characteristics. Since BIM models are manually created during the planning and construction phase, they are only available for newly planned or recently constructed buildings. In order to apply the new applications to already existing buildings, methods for the acquisition of BIM models for built-up sites are required. Primary data source are 3D geometry models obtained from surveying, CAD, or computer graphics. Automation of this process is highly desirable, but faces a range of specific problems setting the bar very high for a reconstruction process. This paper discusses these problems and identifies consequential requirements on reconstruction methods. Above, a two-step strategy for BIM model reconstruction is proposed which incorporates CityGML as an intermediate layer between 3D graphics models and IFC/BIM models.